Seasonal climate and crop forecasts for agricultural risk management
Training related to the Climate Predictability Tool (CPT)
25–27 April 2013 at CIAT, Cali-Colombia
The Climate Predictability Tool (CPT) is a package that facilitates the construction of seasonal climate forecast
models, investigations into model validation and producing forecasts given updated data. The CPT design has been
tailored to produce seasonal climate forecasts using model output statistic corrections to climate predictions from
general circulation models, or to produce forecasts using fields of sea-surface temperatures. Although the
software is specifically tailored for these applications, it can also be used in more general settings to perform
canonical correlation analysis or principal components regression on any data for any application.
Limited work has been done regarding the usage of crop models coupled with seasonal climate forecasts across
the Andean Region. There is a significant opportunity to reduce the production risks inherent to rainfed agriculture
in the low-input systems of the Andes by means of the timely dissemination of seasonal crop yield predictions to
farmers and government officers. When reliable climate forecasts are available, farmers may modify when, how
and what they plant accordingly and they may also use this information to decide on the type of management
practices applied to a given cropping system. This in turn should lower the production risks imposed by climate
variability and result in increased agricultural output. However, coupling crop models with seasonal climate
forecasts for farming applications is a challenging task. This is because most crop models have been developed
under optimal experimental, rather than on-farm, conditions and also because of the inherent errors and
uncertainties in both climate and crop modeling.
The project "Seasonal climate forecasts for agricultural crop and risk management" was jointly developed by the
International Center for Tropical Agriculture (CIAT) and the National Institute for Space Research (INPE), Brazil,
under the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) and Colombia´s
Ministry of Agriculture and Rural Development (MADR). Within the project, we propose the development of a
methodology that combines the seasonal climate forecasts of the regional climate Eta Model, maintained by INPE,
with the Climate Predictability Tool (CPT), developed by the International Research Institute for Climate and
Society (IRI), as a starting point to produce seasonal forecasts of crop productivity. The tool is hereby proposed and
tested for operational use and for further use in climate variability studies.
One of the focal activities carried out under the project is the training course “Seasonal climate forecast, using the
CPT: Statistical methods and forecast quality” to be held at CIAT headquarters in Cali, Colombia, 25–27 April. The
participating institutions include: the International Potato Center (CIP); the Institute of Hydrology, Meteorology
and Environmental Studies (IDEAM), Colombia; MADR, INPE, and CIAT. The objectives of the training are to:
1. Provide a complete introduction to and training in the use of the Climate Predictability Tool (CPT), given
by an IRI scientist. Followed by discussions on the use of the CPT in crop yield forecasting, procedures to
combine the CPT with other outputs and possible strategies for improving seasonal prediction quality.
2. Establish the necessary inter-institutional links to facilitate collaboration on the application of seasonal
climate forecasts on agricultural risk management.
3. Construct methodology to apply seasonal climate forecasts with the CPT to improve agricultural yield
Anthony Barnston. Prior to arriving to IRI at the end of June 2000, Barnston was an
operational seasonal climate forecaster and developmental researcher in empirical
prediction methodology at the Climate Prediction Center of the National Oceanic and
Atmospheric Administration (NOAA), USA, for 17 years. He has authored atlases, reports, and
journal papers on weather and climate, many of which are about statistical diagnoses of
large-scale circulation patterns and on empirical climate prediction. He was editor of the
Experimental Long Lead Forecast Bulletin from 1992 to 1997. Barnston has received awards
from the Department of Commerce and the American Meteorological Society.
Angélica Giarolla. PhD in Agricultural Engineering from the State University of Campinas,
Brazil. With experience in agro-meteorology, crop modeling, climatic risk in agriculture,
weather forecast for agriculture and climate change. She is currently working at the Center
for Earth System Science, National Institute for Space Research (CCST/INPE), Brazil.
Néstor Hernández Iglesias. MSc in Physical Oceanography, from the University of Gdańsk,
Poland. He has great professional experience, with positions in both public and private
sectors, where he has been able to demonstrate and utilize his know-how in diverse topics,
such as technological development in agriculture, research, innovation and technology
transfer, food security, international relationships and trade, with special emphasis in
climate change, weather variability, and environmental sustainability of agricultural projects.
Since 2008, he has worked for Colombiaʼs Ministry of Agriculture and Rural Development.
Valesca Rodriguez Fernandes. MSc in Meteorology from the Federal University of Alagoas.
Experienced in agro-meteorology and atmospheric modeling, Valesca is currently working at
the Center for Weather Forecast and Climate Studies, National Institute for Space Research
José Francisco Boshell. MSc in Agricultural Meteorology, University of Nebraska, USA. Expert
in Agricultural Meteorology at the World Meteorological Organization (Uruguay, Honduras,
Guatemala, Colombia). Consultant in Agricultural Climatology at Colombiaʼs National
Planning Department (DNP); Colombian Corporation for Agricultural Research (CORPOICA);
International Center for Tropical Agriculture (CIAT); German Agency for International
Cooperation (GIZ); Food and Agriculture Organization of the United Nations (FAO);
International Center for El Niño Event Research (CIIFEN). Associate Professor at the National
University of Colombia (UNAL). Technical Secretary of the Inter-Institutional Network for
Climate Change and Food Security (RICCLISA).
Felipe de Mendiburu. A statistician who worked as a researcher at the International Potato
Center (CIP) from 1994 to 2012, with a masters degree in Systems Engineering (National
Engineering University, Peru) and Certified by the American Society for Quality (ASQ), USA,
in Six Sigma Green Belt. Felipe is currently working in CIPʼs Production Systems and
Environment Sub-program. Since 1978, he is a professor in Applied Statistics, Numerical
Methods, and Computer Systems at the National Agrarian University La Molina, Peru.
Author and maintainer of the AGRICOLAE package on the R-Project since 2006.
Diana Giraldo. A Research Assistant of the International Center for Tropical Agriculture
(CIAT) and the International Potato Center (CIP), with an MSc in Meteorology from the
National Agrarian University La Molina, Peru, with a special focus in using seasonal climate
forecasts in Latin America. She brings her knowledge and experience in agro-climatic
models, climate change scenarios, coupling crop models with seasonal climate forecasts and
adaptation/mitigation strategies to quantify potential climate impacts.
Gloria Leoón. A meteorologist with strong experience in observational and climatological
studies, weather forecasting, and climate prediction. Knowledgeable in numerical weather
prediction (NWP), climate models, and radiation models. Professional in interdisciplinary
projects for implementation, operation, and analysis of numerical models, such as WRF,
MM5, CAM, TUV, and development of statistical models for seasonal climate prediction in
Colombia. Consultant to the Institute of Hydrology, Meteorology and Environmental Studies
(IDEAM) and International Center for Tropical Agriculture (CIAT)
Carlos Navarro. A Research Assistant of CIATʼs Decision and Policy Analysis (DAPA) Research
Area. He graduated as an Agricultural Engineer from the National University of Colombia. He
has 2 years experience working at CIAT and his research has focused on climate modeling,
global climate models validation, generation of regional future climate scenarios and
downscaling techniques, necessary for assessing the impacts of climate change on
agriculture and planning adaptive strategies on crops.
David Arango. A statistician with experience in processing data for statistical modeling
studies, sampling, and spatial analysis. David currently works in CIATʼs DAPA Research Area.
Qualified in g